F Acernese et al 2007 Class. Quantum Grav. 24 S415 doi:10.1088/0264-9381/24/19/S05
F Acernese1, P Amico2, M Alshourbagy3, F Antonucci4, S Aoudia5, P Astone4, S Avino1, D Babusci6, G Ballardin7, F Barone1, L Barsotti3, M Barsuglia8, Th S Bauer9, F Beauville10, S Bigotta3, S Birindelli3, M A Bizouard8, C Boccara11, F Bondu5, L Bosi2, C Bradaschia3, S Braccini3, F J van den Brand9, A Brillet5, V Brisson8, D Buskulic10, E Calloni1, E Campagna12, F Carbognani7, F Cavalier8, R Cavalieri7, G Cella3, E Cesarini12, E Chassande-Mottin5, N Christensen7, C Corda3, A Corsi4, F Cottone2, A-C Clapson8, F Cleva5, J-P Coulon5, E Cuoco7, A Dari2, V Dattilo7, M Davier8, M del Prete3, R De Rosa1, L Di Fiore1, A Di Virgilio3, B Dujardin5, A Eleuteri1, M Evans7, I Ferrante3, F Fidecaro3, I Fiori7, R Flaminio7,10, J-D Fournier5, S Frasca4, F Frasconi3, L Gammaitoni2, F Garufi1, E Genin7, A Gennai3, A Giazotto3, G Giordano6, L Giordano1, R Gouaty10, D Grosjean10, G Guidi12, S Hamdani7, S Hebri7, H Heitmann5, P Hello8, D Huet7, S Karkar10, S Kreckelbergh8, P La Penna7, M Laval5, N Leroy8, N Letendre10, B Lopez7, Lorenzini12, V Loriette11, G Losurdo12, J-M Mackowski13, E Majorana4, C N Man5, M Mantovani3, F Marchesoni2, F Marion10, J Marque7, F Martelli12, A Masserot10, M Mazzoni12, L Milano1, F Menzinger7, C Moins7, J Moreau11, N Morgado13, B Mours10, F Nocera7, C Palomba4, F Paoletti3,7, S Pardi1, A Pasqualetti7, R Passaquieti3, D Passuello3, F Piergiovanni12, L Pinard13, R Poggiani3, M Punturo2, P Puppo4, S van der Putten9, K Qipiani1, P Rapagnani4, V Reita11, A Remillieux13, F Ricci4, I Ricciardi1, P Ruggi7, G Russo1, S Solimeno1, A Spallicci5, M Tarallo3, M Tonelli3, A Toncelli3, E Tournefier10, F Travasso2, C Tremola3, G Vajente3, D Verkindt10, F Vetrano12, A Viceré12, J-Y Vinet5, H Vocca2 and M Yvert10
Show affiliationsVirgo started collecting science data during weekends in order to not interfere with commissioning activities. The goal of Weekly Science Runs is to ease the transition between commissioning periods and data taking periods, in addition to providing data sets exploiting the stationary behavior of the detector. The detection of gravitational wave (GW) bursts emitted by core collapse of supernovae is one of the most difficult tasks for the GW community due to the fact that there are uncertainties in the exact shape of the waveforms, as we do not have complete models. A major task for this kind of detection effort is the cleaning of the event triggers found by the detection pipelines, namely the removal of accidental transient signals due to noise source events. In order to clean our data from false GW events, we need to define a strategy for data quality cut and veto of auxiliary and environmental monitoring channels. In this paper we report on the analysis we performed on data acquired during Weekly Science Runs to explore and define the data quality cut and veto studies for burst analysis.
04.80.Nn Gravitational wave detectors and experiments
97.10.Cv Stellar structure, interiors, evolution, nucleosynthesis, ages
Issue 19 (7 October 2007)
Received 13 April 2007, in final form 27 July 2007
Published 19 September 2007
F Acernese et al 2007 Class. Quantum Grav. 24 S415
Sergey Stolbov et al 2009 J. Phys.: Condens. Matter 21 474226
A Ghobeity et al 2007 J. Micromech. Microeng. 17 2175
Zai-Qiao Bai and Wei-Mou Zheng 2003 J. Phys. A: Math. Gen. 36 2737
Shih-Ping Lai et al. 2002 ApJ 566 925
Chen Yu et al 2009 Chinese Phys. Lett. 26 112502
J. C. Cersosimo et al. 2007 ApJ 656 248
Daniel Proga and Mitchell C. Begelman 2003 ApJ 592 767
Dong-Seok Yang et al 2009 J. Phys.: Conf. Ser. 190 012139
Ion I Cotaescu and Mihai Visinescu 2001 Class. Quantum Grav. 18 3383